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Good enough practices in scientific computing

5 references·14 citing·48 second hopsampled

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References

1956The magical number seven, plus or minus two: Some limits on our capacity for processing information.17,866 cited
1994The magical number seven, plus or minus two: Some limits on our capacity for processing information.17,469 cited
2013Ten Simple Rules for Reproducible Computational Research935 cited
2014Best Practices for Scientific Computing727 cited
2009A Quick Guide to Organizing Computational Biology Projects102 cited

Cited by

2018Exploration and Explanation in Computational Notebooks347 cited
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2018Identifying and Overcoming Threats to Reproducibility, Replicability, Robustness, and Generalizability in Microbiome Research281 cited
2019Ten simple rules for writing and sharing computational analyses in Jupyter Notebooks196 cited
2020Garbage in, garbage out?167 cited
2017Four simple recommendations to encourage best practices in research software143 cited
2020Ten simple rules for writing Dockerfiles for reproducible data science125 cited
2018Reproducible research and GIScience: an evaluation using AGILE conference papers122 cited
2017Ten simple rules for making research software more robust119 cited

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2018Re-run, Repeat, Reproduce, Reuse, Replicate: Transforming Code into Scientific Contributions118 cited

2019EviAtlas: a tool for visualising evidence synthesis databases112 cited

2021“Garbage in, garbage out” revisited: What do machine learning application papers report about human-labeled training data?102 cited

2023The five pillars of computational reproducibility: bioinformatics and beyond100 cited

2017A prototype cloud-based reproducible data analysis and visualization platform for outputs of agent-based models6 cited